| dc.contributor | 資訊科學系 | - |
| dc.creator (作者) | Chang, Yung-Chun;Hsieh, Yu-Lun;Chen, Cen-Chieh;Hsu, Wen-Lian | - |
| dc.date (日期) | 2017-01 | - |
| dc.date.accessioned | 27-Aug-2015 17:17:22 (UTC+8) | - |
| dc.date.available | 27-Aug-2015 17:17:22 (UTC+8) | - |
| dc.date.issued (上傳時間) | 27-Aug-2015 17:17:22 (UTC+8) | - |
| dc.identifier.uri (URI) | http://nccur.lib.nccu.edu.tw/handle/140.119/77997 | - |
| dc.description.abstract (摘要) | Detecting the topic of documents can help readers construct the background of the topic and facilitate document comprehension. In this paper, we propose a semantic frame-based topic detection (SFTD) that simulates such process in human perception. We take advantage of multiple knowledge sources and extracted discriminative patterns from documents through a highly automated, knowledge-supported frame generation and matching mechanisms. Using a Chinese news corpus containing over 111,000 news articles, we provide a comprehensive performance evaluation which demonstrates that our novel approach can effectively detect the topic of a document by exploiting the syntactic structures, semantic association, and the context within the text. Experimental results show that SFTD is comparable to other well-known topic detection methods. | - |
| dc.format.extent | 4801735 bytes | - |
| dc.format.mimetype | application/pdf | - |
| dc.relation (關聯) | Soft Computing, Volume 21, Issue 2, pp 391–401 | - |
| dc.subject (關鍵詞) | Topic detection;Semantic frame;Semantic class;Partial matching | - |
| dc.title (題名) | A semantic frame-based intelligent agent for topic detection | - |
| dc.type (資料類型) | article | en |
| dc.identifier.doi (DOI) | 10.1007/s00500-015-1695-4 | - |
| dc.doi.uri (DOI) | http://dx.doi.org/10.1007/s00500-015-1695-4 | - |
